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Model-Based Clustering and Classification for Data Science - With Applications in R (Hardcover) Loot Price: R1,302
Discovery Miles 13 020
You Save: R74 (5%)
Model-Based Clustering and Classification for Data Science - With Applications in R (Hardcover): Charles Bouveyron, Gilles...

Model-Based Clustering and Classification for Data Science - With Applications in R (Hardcover)

Charles Bouveyron, Gilles Celeux, T. Brendan Murphy, Adrian E. Raftery

Series: Cambridge Series in Statistical and Probabilistic Mathematics

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List price R1,376 Loot Price R1,302 Discovery Miles 13 020 | Repayment Terms: R121 pm x 12* You Save R74 (5%)

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Cluster analysis finds groups in data automatically. Most methods have been heuristic and leave open such central questions as: how many clusters are there? Which method should I use? How should I handle outliers? Classification assigns new observations to groups given previously classified observations, and also has open questions about parameter tuning, robustness and uncertainty assessment. This book frames cluster analysis and classification in terms of statistical models, thus yielding principled estimation, testing and prediction methods, and sound answers to the central questions. It builds the basic ideas in an accessible but rigorous way, with extensive data examples and R code; describes modern approaches to high-dimensional data and networks; and explains such recent advances as Bayesian regularization, non-Gaussian model-based clustering, cluster merging, variable selection, semi-supervised and robust classification, clustering of functional data, text and images, and co-clustering. Written for advanced undergraduates in data science, as well as researchers and practitioners, it assumes basic knowledge of multivariate calculus, linear algebra, probability and statistics.

General

Imprint: Cambridge UniversityPress
Country of origin: United Kingdom
Series: Cambridge Series in Statistical and Probabilistic Mathematics
Release date: August 2019
Authors: Charles Bouveyron • Gilles Celeux • T. Brendan Murphy • Adrian E. Raftery
Dimensions: 260 x 185 x 25mm (L x W x T)
Format: Hardcover
Pages: 446
ISBN-13: 978-1-108-49420-5
Categories: Books > Social sciences > Sociology, social studies
Books > Business & Economics > Economics
Books > Medicine > General issues
Books > Science & Mathematics > Mathematics
Books > Computing & IT > Applications of computing
Books > Social sciences > Sociology, social studies > Social research & statistics
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Books > Medicine > General issues > Public health & preventive medicine
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Books > Computing & IT > Applications of computing > Databases
Books > Computing & IT > Applications of computing > Artificial intelligence
Books > Social sciences > Sociology, social studies > Social research & statistics > General
Books > Business & Economics > Economics > Econometrics > Economic statistics
Books > Medicine > General issues > Public health & preventive medicine > Epidemiology & medical statistics
Books > Computing & IT > Applications of computing > Databases > Data capture & analysis
Books > Computing & IT > Applications of computing > Databases > Data mining
Books > Computing & IT > Applications of computing > Artificial intelligence > Machine learning
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LSN: 1-108-49420-X
Barcode: 9781108494205

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